2019-01-16 19:40:08 +00:00
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#
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# Author: Piyush Agram
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# Copyright 2016
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#
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import numpy as np
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import os
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import isceobj
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import logging
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from isceobj.Util.ImageUtil import ImageLib as IML
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import datetime
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import pprint
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from .runFineResamp import getRelativeShifts
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def multilook(intname, alks=5, rlks=15):
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'''
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Take looks.
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'''
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from mroipac.looks.Looks import Looks
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inimg = isceobj.createImage()
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inimg.load(intname + '.xml')
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spl = os.path.splitext(intname)
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ext = '.{0}alks_{1}rlks'.format(alks, rlks)
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outFile = spl[0] + ext + spl[1]
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lkObj = Looks()
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lkObj.setDownLooks(alks)
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lkObj.setAcrossLooks(rlks)
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lkObj.setInputImage(inimg)
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lkObj.setOutputFilename(outFile)
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lkObj.looks()
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print('Output: ', outFile)
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return outFile
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def multilook_old(intName, alks=5, rlks=15):
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cmd = 'looks.py -i {0} -a {1} -r {2}'.format(intName,alks,rlks)
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flag = os.system(cmd)
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if flag:
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raise Exception('Failed to multilook %s'%(intName))
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spl = os.path.splitext(intName)
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return '{0}.{1}alks_{2}rlks{3}'.format(spl[0],alks,rlks,spl[1])
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def overlapSpectralSeparation(topBurstIfg, botBurstIfg, masterTop, masterBot, slaveTop, slaveBot, azTop, rgTop, azBot, rgBot, misreg=0.0):
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'''
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Estimate separation in frequency due to unit pixel misregistration.
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'''
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dt = topBurstIfg.azimuthTimeInterval
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topStart = int(np.round((topBurstIfg.sensingStart - masterTop.sensingStart).total_seconds() / dt))
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overlapLen = topBurstIfg.numberOfLines
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botStart = int(np.round((botBurstIfg.sensingStart - masterBot.sensingStart).total_seconds() / dt))
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##############
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# master top : m1
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azi = np.arange(topStart, topStart+overlapLen)[:,None] * np.ones((overlapLen, topBurstIfg.numberOfSamples))
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rng = np.ones((overlapLen, topBurstIfg.numberOfSamples)) * np.arange(topBurstIfg.numberOfSamples)[None,:]
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Vs = np.linalg.norm(masterTop.orbit.interpolateOrbit(masterTop.sensingMid, method='hermite').getVelocity())
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Ks = 2 * Vs * masterTop.azimuthSteeringRate / masterTop.radarWavelength
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rng = masterTop.startingRange + masterTop.rangePixelSize * rng
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Ka = masterTop.azimuthFMRate(rng)
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Ktm1 = Ks / (1.0 - Ks / Ka)
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tm1 = (azi - (masterTop.numberOfLines//2)) * masterTop.azimuthTimeInterval
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fm1 = masterTop.doppler(rng)
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##############
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# master bottom : m2
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azi = np.arange(botStart, botStart + overlapLen)[:,None] * np.ones((overlapLen, botBurstIfg.numberOfSamples))
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rng = np.ones((overlapLen, botBurstIfg.numberOfSamples)) * np.arange(botBurstIfg.numberOfSamples)[None,:]
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Vs = np.linalg.norm(masterBot.orbit.interpolateOrbit(masterBot.sensingMid, method='hermite').getVelocity())
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Ks = 2 * Vs * masterBot.azimuthSteeringRate / masterBot.radarWavelength
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rng = masterBot.startingRange + masterBot.rangePixelSize * rng
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Ka = masterBot.azimuthFMRate(rng)
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Ktm2 = Ks / (1.0 - Ks / Ka)
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tm2 = (azi - (masterBot.numberOfLines//2)) * masterBot.azimuthTimeInterval
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fm2 = masterBot.doppler(rng)
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##############
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# slave top : s1
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y = np.arange(topStart, topStart+overlapLen)[:,None] * np.ones((overlapLen, topBurstIfg.numberOfSamples))
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x = np.ones((overlapLen, topBurstIfg.numberOfSamples)) * np.arange(topBurstIfg.numberOfSamples)[None,:]
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yy = np.memmap( azTop, dtype=np.float32, mode='r',
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shape=(topBurstIfg.numberOfLines, topBurstIfg.numberOfSamples))
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xx = np.memmap( rgTop, dtype=np.float32, mode='r',
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shape=(topBurstIfg.numberOfLines, topBurstIfg.numberOfSamples))
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azi = y + yy + misreg
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rng = x + xx
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# print('Azi top: ', azi[0,0], azi[-1,-1])
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# print('YY top: ', yy[0,0], yy[-1,-1])
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# print('Rng top: ', rng[0,0], azi[-1,-1])
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# print('XX top: ', xx[0,0], xx[-1,-1])
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Vs = np.linalg.norm(slaveTop.orbit.interpolateOrbit(slaveTop.sensingMid, method='hermite').getVelocity())
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Ks = 2 * Vs * slaveTop.azimuthSteeringRate / slaveTop.radarWavelength
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rng = slaveTop.startingRange + slaveTop.rangePixelSize * rng
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Ka = slaveTop.azimuthFMRate(rng)
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Kts1 = Ks / (1.0 - Ks / Ka)
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ts1 = (azi - (slaveTop.numberOfLines//2)) * slaveTop.azimuthTimeInterval
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fs1 = slaveTop.doppler(rng)
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##############
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# slave bot : s2
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y = np.arange(botStart, botStart + overlapLen)[:,None] * np.ones((overlapLen, botBurstIfg.numberOfSamples))
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x = np.ones((overlapLen, botBurstIfg.numberOfSamples)) * np.arange(botBurstIfg.numberOfSamples)[None,:]
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####Bottom slave
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yy = np.memmap( azBot, dtype=np.float32, mode='r',
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shape=(botBurstIfg.numberOfLines, botBurstIfg.numberOfSamples))
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xx = np.memmap( rgBot, dtype=np.float32, mode='r',
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shape=(botBurstIfg.numberOfLines, botBurstIfg.numberOfSamples))
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azi = y + yy + misreg
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rng = x + xx
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# print('Azi bot: ', azi[0,0], azi[-1,-1])
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# print('YY bot: ', yy[0,0], yy[-1,-1])
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# print('Rng bot: ', rng[0,0], azi[-1,-1])
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# print('XX bot: ', xx[0,0], xx[-1,-1])
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Vs = np.linalg.norm(slaveBot.orbit.interpolateOrbit(slaveBot.sensingMid, method='hermite').getVelocity())
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Ks = 2 * Vs * slaveBot.azimuthSteeringRate / slaveBot.radarWavelength
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rng = slaveBot.startingRange + slaveBot.rangePixelSize * rng
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Ka = slaveBot.azimuthFMRate(rng)
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Kts2 = Ks / (1.0 - Ks / Ka)
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ts2 = (azi - (slaveBot.numberOfLines//2)) * slaveBot.azimuthTimeInterval
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fs2 = slaveBot.doppler(rng)
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##############
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frequencySeparation = -Ktm2*tm2 + Ktm1*tm1 + Kts1*ts1 - Kts2*ts2 + fm2 - fm1 + fs1 -fs2
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# print('Ktm1: ', Ktm1[0,0], Ktm1[-1,-1])
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# print('Ktm2: ', Ktm2[0,0], Ktm2[-1,-1])
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# print('tm1 : ', tm1[0,0], tm1[-1,-1])
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# print('tm2 : ', tm2[0,0], tm2[-1,-1])
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# print('Kts1: ', Kts1[0,0], Kts1[-1,-1])
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# print('Kts2: ', Kts2[0,0], Kts2[-1,-1])
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# print('ts1 : ', ts1[0,0], ts2[-1,-1])
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# print('ts2 : ', ts2[0,0], ts2[-1,-1])
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# print('fm1 : ', fm1[0,0], fm1[-1,-1])
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# print('fm2 : ', fm2[0,0], fm2[-1,-1])
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# print('fs1 : ', fs1[0,0], fs1[-1,-1])
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# print('fs2 : ', fs2[0,0], fs2[-1,-1])
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return frequencySeparation
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def createCoherence(intfile, win=5):
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'''
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Compute coherence using scipy convolve 2D.
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'''
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2019-12-16 18:22:01 +00:00
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import scipy.signal as SS
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2019-01-16 19:40:08 +00:00
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corfile = os.path.splitext(intfile)[0] + '.cor'
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filt = np.ones((win,win))/ (1.0*win*win)
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inimg = IML.mmapFromISCE(intfile + '.xml', logging)
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cJ = np.complex64(1.0j)
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angle = np.exp(cJ * np.angle(inimg.bands[0]))
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res = SS.convolve2d(angle, filt, mode='same')
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res[0:win-1,:] = 0.0
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res[-win+1:,:] = 0.0
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res[:,0:win-1] = 0.0
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res[:,-win+1:] = 0.0
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res = np.abs(res)
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with open(corfile, 'wb') as f:
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res.astype(np.float32).tofile(f)
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img = isceobj.createImage()
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img.setFilename(corfile)
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img.setWidth(res.shape[1])
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img.setLength(res.shape[0])
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img.dataType='FLOAT'
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img.setAccessMode('READ')
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img.renderHdr()
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return corfile
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def runPrepESD(self):
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'''
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Create additional layers for performing ESD.
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'''
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if not self.doESD:
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return
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swathList = self._insar.getValidSwathList(self.swaths)
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for swath in swathList:
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if self._insar.numberOfCommonBursts[swath-1] < 2:
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print('Skipping prepesd for swath IW{0}'.format(swath))
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continue
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minBurst, maxBurst = self._insar.commonMasterBurstLimits(swath-1)
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slaveBurstStart, slaveBurstEnd = self._insar.commonSlaveBurstLimits(swath-1)
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####Load full products
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master = self._insar.loadProduct( os.path.join(self._insar.masterSlcProduct, 'IW{0}.xml'.format(swath)))
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slave = self._insar.loadProduct( os.path.join(self._insar.slaveSlcProduct, 'IW{0}.xml'.format(swath)))
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####Estimate relative shifts
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relShifts = getRelativeShifts(master, slave, minBurst, maxBurst, slaveBurstStart)
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maxBurst = maxBurst - 1 ###For overlaps
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####Load metadata for burst IFGs
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ifgTop = self._insar.loadProduct( os.path.join(self._insar.coarseIfgOverlapProduct, 'top_IW{0}.xml'.format(swath)))
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ifgBottom = self._insar.loadProduct( os.path.join(self._insar.coarseIfgOverlapProduct, 'bottom_IW{0}.xml'.format(swath)))
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print('Relative shifts for swath {0}:'.format(swath))
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pprint.pprint(relShifts)
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####Create ESD output directory
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esddir = self._insar.esdDirname
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2020-04-13 19:40:32 +00:00
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os.makedirs(esddir, exist_ok=True)
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2019-01-16 19:40:08 +00:00
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####Overlap offsets directory
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offdir = os.path.join( self._insar.coarseOffsetsDirname, self._insar.overlapsSubDirname, 'IW{0}'.format(swath))
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ifglist = []
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factorlist = []
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offsetlist = []
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cohlist = []
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for ii in range(minBurst, maxBurst):
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ind = ii - minBurst ###Index into overlaps
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sind = slaveBurstStart + ind ###Index into slave
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topShift = relShifts[sind]
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botShift = relShifts[sind+1]
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topBurstIfg = ifgTop.bursts[ind]
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botBurstIfg = ifgBottom.bursts[ind]
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####Double difference interferograms
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topInt = np.memmap( topBurstIfg.image.filename,
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dtype=np.complex64, mode='r',
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shape = (topBurstIfg.numberOfLines, topBurstIfg.numberOfSamples))
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botInt = np.memmap( botBurstIfg.image.filename,
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dtype=np.complex64, mode='r',
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shape = (botBurstIfg.numberOfLines, botBurstIfg.numberOfSamples))
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intName = os.path.join(esddir, 'overlap_IW%d_%02d.int'%(swath,ii+1))
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freqName = os.path.join(esddir, 'freq_IW%d_%02d.bin'%(swath,ii+1))
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with open(intName, 'wb') as fid:
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fid.write( topInt * np.conj(botInt))
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img = isceobj.createIntImage()
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img.setFilename(intName)
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img.setLength(topBurstIfg.numberOfLines)
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img.setWidth(topBurstIfg.numberOfSamples)
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img.setAccessMode('READ')
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img.renderHdr()
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multIntName= multilook(intName, alks = self.esdAzimuthLooks, rlks=self.esdRangeLooks)
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ifglist.append(multIntName)
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####Estimate coherence of double different interferograms
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multCor = createCoherence(multIntName)
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cohlist.append(multCor)
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####Estimate the frequency difference
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azTop = os.path.join(offdir, 'azimuth_top_%02d_%02d.off'%(ii+1,ii+2))
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rgTop = os.path.join(offdir, 'range_top_%02d_%02d.off'%(ii+1,ii+2))
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azBot = os.path.join(offdir, 'azimuth_bot_%02d_%02d.off'%(ii+1,ii+2))
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rgBot = os.path.join(offdir, 'range_bot_%02d_%02d.off'%(ii+1,ii+2))
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mFullTop = master.bursts[ii]
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mFullBot = master.bursts[ii+1]
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sFullTop = slave.bursts[sind]
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sFullBot = slave.bursts[sind+1]
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freqdiff = overlapSpectralSeparation(topBurstIfg, botBurstIfg, mFullTop, mFullBot, sFullTop, sFullBot, azTop, rgTop, azBot, rgBot)
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with open(freqName, 'wb') as fid:
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(freqdiff * 2 * np.pi * mFullTop.azimuthTimeInterval).astype(np.float32).tofile(fid)
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img = isceobj.createImage()
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img.setFilename(freqName)
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img.setWidth(topBurstIfg.numberOfSamples)
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img.setLength(topBurstIfg.numberOfLines)
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img.setAccessMode('READ')
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img.bands = 1
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img.dataType = 'FLOAT'
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img.renderHdr()
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multConstName = multilook(freqName, alks = self.esdAzimuthLooks, rlks = self.esdRangeLooks)
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factorlist.append(multConstName)
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